Neurodevelopmental disorders (NDDs) often have unknown genetic causes. Current efforts in identifying disease-related genetic variants using exome or genome sequencing still lead to an excessive number of variants of uncertain significance (VUS). There is an increasing interest in transcriptomics and, more recently, proteomics for variant detection and interpretation. In this study, we integrated quantitative liquid chromatography-mass spectrometry proteomics, RNA sequencing, and exome reanalysis to resolve VUS and detect novel causal variants in 34 patients with undiagnosed NDDs, using the software PROTRIDER and DROP to detect protein outliers and RNA outliers, respectively. We obtained a diagnosis in 11 cases (32%) resulting from the increased amount of information provided by the two additional levels of omics (n = 5) and the updated literature evidence (n = 6). Our experience suggests the potential of this outlier-detection multi-omics workflow for improving diagnostic yield in NDDs and other rare disorders.
